[blackle]

Increasing temperature just makes more uncommon tokens more likely to appear. This can include both uncommon ideas and uncommon spelling and grammatical mistakes. It also won't make ideas that the LLM isn't capable of thinking appear, unless you crank the temperature way up and get lucky (like monkeys on typewriters lucky)

[ein0p]

Not just “uncommon tokens”. In the case when generation does weighted random sampling, it autoregressively takes its own past tokens into account. It generates whole different sequences. So if it’s diversity of output you want, you will get it.

[lanstin]

That is also true for creative people. Generating interesting ideas is one thing then filtering out impractical or unaesthetic ideas is also needed.

[dragonwriter]

Right, so in rough outline an LLM-based brainstorming framework might generate multiple responses to a question with multiple different combinations of temperature, top_p, top_k, etc., to get a mix of dull-but-baseline (you don’t want to miss those options) and more off-the-beaten path responses, then take each one and send it back to the LLM with a prompt to evaluate “does this provide a coherent answer – however unconventional or bad of an idea – to the question asked?” to filter out the cases where it was asked for summer vacation ideas and responded with something like “Banana banana banana banana” (this request probably with default tuning.)